Household inequality and the consumption response to aggregate real shocks

Gene Amromin, Mariacristina De Nardi, Karl Schulze04 January 2018

A widening gap between rich and poor has been extensively documented for many countries and economies. This column explores how the wealth gap affects output and consumption changes in response to aggregate shocks. Lower- and higher-wealth households face different borrowing constraints, and have different marginal propensities to consume. Different levels of access to financial liquidity thus play a major role in the overall consumption dynamics during an economic downturn.

The increase in inequality over the last several decades has received widespread attention from both academics and the public at large. While much of this discourse centres on either the causes or the normative implications of increasing inequality, it is important to ask whether the widening gap between rich and poor has any direct effects on macroeconomic aggregates. In particular, we need to understand how the wealth gap affected the severity of the Great Recession, which saw precipitous drops in output and consumption, followed by slow recoveries in both (see Figure 1). Is it possible that the changing distribution of wealth intensified and lengthened the effects of this downturn? More broadly, should economists and policymakers concerned with macroeconomics be worried about wealth inequality?

Our recent working paper argues that the role of borrowing constraints cannot be adequately captured by only having a large share of households with little wealth before a recession, as is currently the case in most macroeconomic theory1 (Amromin et al. 2017).

Krusell and Smith (1998; henceforth KS), propose a model of consumption and savings with incomplete capital markets and aggregate uncertainty, where wealth inequality is the cumulative result of different past labour market experiences. To proxy a recession, the authors induce a negative shock to aggregate productivity, which lowers wages and raises unemployment. This paper teaches us that aggregate consumption can depend on the shape of the wealth distribution, even though price and inflation dynamics only depend on average wealth. The intuition for this duality is that low-wealth households make up a sizeable fraction of consumption and have the largest marginal propensities to consume, while contributing the least to aggregate capital and price determination.

Krueger et al. (2016; henceforth KMP) extend KS’s model to a life-cycle framework and allow for unemployment insurance. Their enriched model endogenously generates much more wealth inequality than the KS baseline economy. The authors compare the dynamics of these two models and find that the KMP version generates a larger drop in consumption in response to a downturn, even after holding the total amount of wealth in the economy fixed. Thus, increasing wealth inequality can increase the severity of a recession.

These two important papers provide convincing evidence that inequality can worsen the negative effects of a recession. However, these models still miss some important aspects of the data that characterised the Great Recession. These features include endogenous changes to wealth due to changes in asset and house prices, the composition of asset holdings, the tightening of credit standards, and the complex earnings dynamics of those who remain employed. Taking into consideration these additional elements can help provide a better picture of who is borrowing constrained and how their consumption changes when they are hit by a shock.

The goal of our paper is to highlight these trends using the Panel Study of Income Dynamics (PSID) and Credit Bureau Panel Data (Equifax) data. The PSID is a widely used and study of a nationally representative panel of households that observes their wealth, earnings, and consumption every two years in our data, which cover from 2000 to 2012. Equifax is a nationally representative sample of individual borrowers, containing data on all aspects of individual and household-level borrowing and credit. These datasets allow us to characterise the experience of households prior to and during the recession.

First, the models we discussed so far do not have the sizable wealth losses due to the changing asset and house values that were observed during the Great Recession. In the data, the wealth distribution shifted sharply leftward between 2006 and 2010, with the share of households holding negative net worth jumping from 16% to 24%. Moreover, the PSID shows us that changes in net worth have consequences for a household’s consumption levels. In Figure 2, we follow households in the middle 20% of 2006 net worth, defined as holding between $37,400 and $133,000, as they transition across fixed wealth quintiles in 2010. We find that downward movements in wealth are associated with negative consumption growth rates. For example, 43.8% of households remain in this group in 2010 (Q3 to Q3 in the figure), and they experience a 0.9% per year increase in consumption. In contrast, 12.5% of households who held this level of wealth in 2006 dropped to the bottom 20% of wealth (Q3 to Q1). This group had an average nominal net worth of $73,900 in 2006 and dropped to a 2010 mean of -$33,100 in 2010. They also experienced an annualised -2.8% decline in nominal consumption. Similarly, for the Q3 to Q2 group, 22.9% of households dropped from an average wealth level of $73,000 to $20,800 and experienced a -3.3% annualised decline in consumption. Therefore, asset and home values appear to play an important role in a household’s consumption and saving decisions.

Figure 2 Nominal household consumption changes

Notes: Annualised nominal consumption changes (%) across 2010 net worth quintiles, for households starting in the third net worth quintile in 2006 ($37,400–$133,000), and moving to any net worth quintile in 2010 (PSID).

Second, these models abstract from portfolio choice and the important observation that the composition of household assets changes over the wealth distribution. For example, in the PSID, only 12.7% of families in the lowest wealth quintile in 2006 owned their home, compared to 80.2% in the middle quintile. Similarly, 82.7% of families at the top of the wealth distribution held financial assets, compared with 33.6% in the middle quintile. Thus, the collapse of the housing bubble affected households differently across the wealth distribution. We calculate that 22% of families in the middle of the wealth distribution lost all of their housing wealth, compared to only 6.5% at the top quintile. In contrast, low-wealth households were less affected by housing price declines, since so few owned a home.

Third, the decline in asset prices and rise in unemployment occurred simultaneously with a tightening of credit standards. Guerrieri and Lorenzoni (2017) show that this also tends to reduce consumption. With the onset of the recession, not only did many households’ credit scores decline, but financial institutions also raised their required credit score thresholds, with the median score of borrowers approved for mortgages backed by Fannie Mae or Freddie Mac increasing from 720 to 780. The result of this tightening was that only super-prime borrowers – that is, those with credit scores above 779 – did not see substantial declines in their success rates of obtaining credit. Importantly, for the various measures we consider in Figure 3, this deterioration in the ability of households to borrow appears not to have recovered as of 2012, possibly contributing to the slow recovery that we have observed.

Fourth, the models only consider increases in the risk of unemployment during recessions, which tend to affect those at the bottom of the wealth distribution the most. However, in the data, changes in hours worked and earnings for those who remain employed also show substantial declines that play out differently across the wealth distribution. Downward changes in households’ earnings expectations can also help explain the slow recovery of consumption after the crisis, amplifying the intensity of the initial downturn. For example, Pistaferri (2016) shows that declines in consumer confidence and earnings expectations explain the longer-than-normal recovery in expenditures, especially among those at the bottom of the income distribution. De Nardi et al. (2012) show that the recession was characterised by both permanent shocks to income and increases in income uncertainty, while Malmendier and Nagel (2011) use evidence from those who experienced the Great Depression to show that a financial crisis can permanently increase risk-aversion among households who live through them.

The models of KS and KMP, together with these additional insights from the data, point to the importance of thinking about borrowing constraints and marginal propensities to consume in frameworks where the constraints are not simply synonymous with simply having a low net worth. The models also stress the consequences that unequal access to financial liquidity can have on consumption dynamics during an economic downturn. As we show, various measures of household constraints have permanently increased in the wake of the Great Recession (Figure 3), raising the need for caution in thinking about an economy’s response to aggregate shocks.

Authors’ note: The views expressed here are not necessarily those of the Federal Reserve Bank of Chicago or the Federal Reserve System, the NBER, the CEPR, or IFS.